HARK
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econ-ark
Heterogenous Agents Resources & toolKit
DWC pointed out that MarkovConsumerType doesn't work "off the shelf". This PR fixes that with a new custom income process constructor. Tests run correctly, but example notebooks might break, let's...
- [ ] Tests for new functionality/models or Tests to reproduce the bug-fix in code. - [ ] Updated documentation of features that add new functionality. - [ ] Update...
Changing many variables for agents changes their initial assets even when they haven't died, there's no uncertainty, and the change is only for parameter events that have happened before the...
Per meeting on 8/14, CDC wants users to be able to specify idiosyncratic permanent income growth rather than overall permanent income growth. This commit adds a constructor method that combines...
The `limit` attribute of DiscreteDistribution instances links to the underlying continuous distribution from which it was generated, and also has information about the discretization parameters. There's still some work to...
**Describe the bug** When you search for Cycles_tutorial in docs.econ-ark.org, it is not found. **To Reproduce** Steps to reproduce the behavior: 1. Go to 'docs.econ-ark.org' 2. Click on either 'Overview...
``` from HARK.distribution import expected, Normal, DiscreteDistributionLabeled import numpy as np gamma = DiscreteDistributionLabeled.from_unlabeled( Normal(mu= 0, sigma = 1).discretize(**{"N" : 7}), var_names=["gamma"] ) expected(func=lambda x: x['gamma'] * np.array([1,2]), dist=gamma) ```...
This code: ``` from HARK.distribution import expected, Normal, DiscreteDistributionLabeled gamma = DiscreteDistributionLabeled.from_unlabeled( Normal(mu= 0, sigma = 1).discretize(**{"N" : 7}), var_names=["gamma"] ) expected(func=lambda x: x, dist=gamma, labels=True) ``` Gets this error:...
`calc_expectation` returns the expected value of a function over a distribution. https://github.com/econ-ark/HARK/blob/master/HARK/distribution.py#L2298 It isn't yet implemented to be compatible with Labelled distributions: https://github.com/econ-ark/HARK/blob/master/HARK/distribution.py#L1450 It probably can be written to wrap...
Please ensure your pull request adheres to the following guidelines: - [ ] Tests for new functionality/models or Tests to reproduce the bug-fix in code. - [ ] Updated documentation...
